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» Modeling Relational Data as Graphs for Mining
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SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
13 years 7 months ago
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guil...
KDD
2006
ACM
143views Data Mining» more  KDD 2006»
16 years 4 months ago
Mining long-term search history to improve search accuracy
Long-term search history contains rich information about a user's search preferences. In this paper, we study statistical language modeling based methods to mine contextual i...
Bin Tan, Xuehua Shen, ChengXiang Zhai
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 4 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
KDD
2008
ACM
142views Data Mining» more  KDD 2008»
16 years 4 months ago
Weighted graphs and disconnected components: patterns and a generator
The vast majority of earlier work has focused on graphs which are both connected (typically by ignoring all but the giant connected component), and unweighted. Here we study numer...
Mary McGlohon, Leman Akoglu, Christos Faloutsos
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
15 years 6 months ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang